An adaptive random search for short term generation scheduling with network constraints.

ABSTRACT: This paper presents an adaptive random search approach to address a short term generation scheduling with network constraints, which determines the startup and shutdown schedules of thermal units over a given planning horizon. In this model, we consider the transmission network through capacity limits and line losses. The mathematical model is stated in the form of a Mixed Integer Non Linear Problem with binary variables. The proposed heuristic is a population-based method that generates a set of new potential solutions via a random search strategy. The random search is based on the Markov Chain Monte Carlo method. The main key of the proposed method is that the noise level of the random search is adaptively controlled in order to exploring and exploiting the entire search space. In order

SUBMITTER: Marmolejo JA 

PROVIDER: S-EPMC5325276 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature